Search results for " observation."

English pronunciation teaching in Finland

2013

Directly Observed Physical Activity among 3-Year-Olds in Finnish Childcare

2014

The main purpose of the study was to determine 3-year-olds’ physical activity levels and how these vary across season, gender, time of day, location, and the physical and social environment in childcare settings in Finland. A modified version of the Observational System for Recording Physical Activity in Children-Preschool (OSRAC-P) was used to measure physical activity levels and contextual variables (e.g., group composition, prompts) of children attending childcare centres. In total, 81 children (42 boys and 39 girls) were observed in autumn and in winter. Three-level linear regression analyses were used to assess differences between the seasons in the association between the context vari…

Post-fire practices benefits on vegetation recovery and soil conservation in a Mediterranean area

2021

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG. [Abstract] Post-fire practices (PFP) aim to reduce soil erosion and favour vegetation recovery, but their effectiveness is spatially heterogeneous and under debate because of the economic and environmental costs. This study evaluates the different changes (Δ) of canopy cover (CC), sediment connectivity (SC) and local topography in four areas affected by the Pinet fire in eastern Spain (August 8th, 2018) and managed with: totally burnt with tree removal and long log erosion barriers (LEBs) (Pinet-1), partially burnt without PFP (Pinet-2), totally burnt with tree removal and short LEBs (Pinet-3), and totally burnt wit…

A Survey of Active Learning for Quantifying Vegetation Traits from Terrestrial Earth Observation Data

2021

The current exponential increase of spatiotemporally explicit data streams from satellite-based Earth observation missions offers promising opportunities for global vegetation monitoring. Intelligent sampling through active learning (AL) heuristics provides a pathway for fast inference of essential vegetation variables by means of hybrid retrieval approaches, i.e., machine learning regression algorithms trained by radiative transfer model (RTM) simulations. In this study we summarize AL theory and perform a brief systematic literature survey about AL heuristics used in the context of Earth observation regression problems over terrestrial targets. Across all relevant studies it appeared that…

Vegetation Types Mapping Using Multi-Temporal Landsat Images in the Google Earth Engine Platform

2021

Vegetation Types (VTs) are important managerial units, and their identification serves as essential tools for the conservation of land covers. Despite a long history of Earth observation applications to assess and monitor land covers, the quantitative detection of sparse VTs remains problematic, especially in arid and semiarid areas. This research aimed to identify appropriate multi-temporal datasets to improve the accuracy of VTs classification in a heterogeneous landscape in Central Zagros, Iran. To do so, first the Normalized Difference Vegetation Index (NDVI) temporal profile of each VT was identified in the study area for the period of 2018, 2019, and 2020. This data revealed strong se…

Comparative analysis of atmospheric radiative transfer models using the Atmospheric Look-up table Generator (ALG) toolbox (version 2.0)

2019

Abstract. Atmospheric radiative transfer models (RTMs) are software tools that help researchers in understanding the radiative processes occurring in the Earth's atmosphere. Given their importance in remote sensing applications, the intercomparison of atmospheric RTMs is therefore one of the main tasks used to evaluate model performance and identify the characteristics that differ between models. This can be a tedious tasks that requires good knowledge of the model inputs/outputs and the generation of large databases of consistent simulations. With the evolution of these software tools, their increase in complexity bears implications for their use in practical applications and model interco…

A Survey on Gaussian Processes for Earth-Observation Data Analysis: A Comprehensive Investigation

2016

Gaussian processes (GPs) have experienced tremendous success in biogeophysical parameter retrieval in the last few years. GPs constitute a solid Bayesian framework to consistently formulate many function approximation problems. This article reviews the main theoretical GP developments in the field, considering new algorithms that respect signal and noise characteristics, extract knowledge via automatic relevance kernels to yield feature rankings automatically, and allow applicability of associated uncertainty intervals to transport GP models in space and time that can be used to uncover causal relations between variables and can encode physically meaningful prior knowledge via radiative tra…

Clasificación de usos del suelo a partir de imágenes Sentinel-2

2017

[EN] Sentinel-2 (S2), a new ESA satellite for Earth observation, accounts with 13 bands which provide high-quality radiometric images with an excellent spatial resolution (10 and 20 m) ideal for classification purposes. In this paper, two objectives have been addressed: to determine the best classification method for S2, and to quantify its improve-ment with respect to the SPOT operational mission. To do so, four classifiers (LDA, RF, Decision Trees, K-NN) have been selected and applied to two different agricultural areas located in Valencia (Spain) and Buenos Aires (Argentina). All classifiers were tested using, on the one hand, all the S2 bands and, on the other hand, only selecting those…

The Indian-French Trishna Mission: Earth Observation in the Thermal Infrared with High Spatio-Temporal Resolution

2018

International audience; The monitoring of the water cycle at the Earth surface which tightly interacts with the climate change processes as well as a number of practical applications (agriculture, soil and water quality assessment, irrigation and water resource management, etc...) requires surface temperature measurements at local scale. Such is the goal of the Indian-French high spatio-temporal TRISHNA mission (Thermal infraRed Imaging Satellite for High-resolution Natural resource Assessment). The scientific objectives of the mission and research work conducted to consolidate the mission specifications are presented. Progress in modelling of surface fluxes is then discussed. The main spec…

A Critical Comparison of Remote Sensing Leaf Area Index Estimates over Rice-Cultivated Areas: From Sentinel-2 and Landsat-7/8 to MODIS, GEOV1 and EUM…

2018

Leaf area index (LAI) is a key biophysical variable fundamental in natural vegetation and agricultural land monitoring and modelling studies. This paper is aimed at comparing, validating and discussing different LAI satellite products from operational services and customized solution based on innovative Earth Observation (EO) data such as Landsat-7/8 and Sentinel-2A. The comparison was performed to assess overall quality of LAI estimates for rice, as a fundamental input of different scale (regional to local) operational crop monitoring systems such as the ones developed during the "An Earth obseRvation Model based RicE information Service" (ERMES) project. We adopted a multiscale approach f…